Data Science & ML MCP 服务器
发现我们为 data science & ml 精心策划的 MCP 服务器集合。浏览 4411 个服务器,找到满足您需求的完美 MCP。
Deep Research
Leverage any Large Language Model to generate comprehensive, privacy-focused research reports.
Code Interpreter API
Provides an open-source implementation of the ChatGPT Code Interpreter using LangChain for sandboxed Python code execution.
Langroid
Enables building LLM-powered applications through a multi-agent programming paradigm.
GPT Code
Provides an open-source implementation of OpenAI's ChatGPT Code interpreter, enabling users to generate and execute code through natural language prompts.
Claude Context
Enhances AI coding agents by providing semantic code search and deep context from an entire codebase.
Simple AIChat
Provides a streamlined Python interface for easily interacting with AI chat models like ChatGPT and GPT-4, emphasizing efficiency and minimal code complexity.
OP Vault
Empower ChatGPT with long-term memory by creating custom knowledge bases from uploaded documents and retrieving relevant answers using the OpenAI and Pinecone vector database stack.
MiniMax-01
Provides access to large language and vision-language models based on linear attention for various natural language and multimodal tasks.
Genkit
Build AI-powered applications with this open-source framework for Node.js and Go.
Fast Agent
Defines, prompts, and tests MCP-enabled agents and workflows.
MCP Chinese Getting Started Guide
Provides a quick start guide for programming with the Model Context Protocol (MCP) in Chinese.
Pollinations
Generates images, text, and audio from text prompts using a free and open-source API.
GenAIScript
Programmatically assembles prompts for LLMs using JavaScript to orchestrate LLMs, tools, and data in code.
Chart Generator
Generates visual charts from data using the Model Context Protocol and AntV.
PromptX
Transforms AI agents into specialized experts through a revolutionary conversational context engineering platform.
Trieve
Provides all-in-one infrastructure for search, recommendations, Retrieval-Augmented Generation (RAG), and analytics via API.
Xiaozhi
Experience AI Xiaozhi's voice and smart assistant functionalities through a versatile Python-based client, enabling access without dedicated hardware.
Google Gen AI
Enables developers to integrate Google's generative models into Python applications.
Java SDK
Enables Java applications to interact with AI models and tools through a standardized interface.
Chain of Recursive Thoughts
Enhances AI model reasoning by making it recursively evaluate and refine its responses through self-argumentation.
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